Community resilience in rural China: the case of Hu Village, Sichuan Province

Building on conceptual frameworks to assess community resilience developed by Emery and Flora (2006) and Kelly et al. (2015), this study analyses the resilience of Hu village (Sichuan, China). The resilience of the village is assessed in the face of multiple and complex slow- and fast onset anthropogenic disturbances, especially the impacts of globalisation and modernisation, which have substantially transformed Chinese society. Hu village is typical for a rural community in transition affected by industrialisation, deagrarianisation, counter-urbanisation and changing stakeholder expectations and opportunities. This has been accompanied by agricultural depopulation, outmigration, increasing non-farm employment, declining agricultural incomes, and associated social and psychological changes – processes that have decreased community resilience. Overall, Hu village emerges as only moderately resilient with tendencies for a further weakening of resilience. While economic, social and cultural domains are (still) moderately resilient, the natural and political domains show weak resilience. Building on critical studies of Chinese rural areas (e.g. Ye and He, 2008; He, 2010; Huang et al., 2010) the study concludes by arguing that Chinese government policies need to be substantially realigned if the resilience of rural communities such as Hu village is to be improved

Pathways towards coexistence with large carnivores in production systems

Coexistence between livestock grazing and carnivores in rangelands is a major challenge in terms of sustainable agriculture, animal welfare, species conservation and ecosystem function. Many effective non-lethal tools exist to protect livestock from predation, yet their adoption remains limited. Using a social-ecological transformations framework, we present two qualitative models that depict transformative change in rangelands grazing. Developed through participatory processes with stakeholders from South Africa and the United States of America, the models articulate drivers of change and the essential pathways to transition from routine lethal management of carnivores towards mutually beneficial coexistence. The pathways define broad actions that incorporate multiple values in grazing systems including changes to livestock management practices, financial support, industry capacity building, research, improved governance and marketing initiatives. A key fnding is the new concept of ‘Predator Smart Farming’, a holistic and conscientious approach to agriculture, which increases the resilience of landscapes, animals (domesticated and wild) and rural livelihoods. Implementation of these multiple pathways would lead to a future system that ensures thriving agricultural communities, secure livelihoods, reduced violence toward animals, and landscapes that are productive and support species conservation and coexistence

Temporal change in UK marine communities : trends or regime shifts?

regime shift is a large, sudden, and long-lasting change in the dynamics of an ecosystem, affecting multiple trophic levels. There are a growing number of papers that report regime shifts in marine ecosystems. However, the evidence for regime shifts is equivocal, because the methods used to detect them are not yet well developed. We have collated over 300 biological time series from seven marine regions around the UK, covering the ecosystem from phytoplankton to marine mammals. Each time series consists of annual measures of abundance for a single group of organisms over several decades. We summarised the data for each region using the first principal component, weighting either each time series or each biological component (e.g. plankton, fish, benthos) equally. We then searched for regime shifts using Rodionov’s regime shift detection (RSD) method, which found regime shifts in the first principal component for all seven marine regions. However, there are consistent temporal trends in the data for six of the seven regions. Such trends violate the assumptions of RSD. Thus, the regime shifts detected by RSD in six of the seven regions are likely to be artefacts caused by temporal trends. We are therefore developing more appropriate time series models for both single populations and whole communities that will explicitly model temporal trends and should increase our ability to detect true regime shift events